Fantasy Football Week 7: Wide Receiver Touchdown Regression Update

Amari Cooper has been strong in fantasy football of late, but should his totals actually be better?

It's true that some players -- I'm looking at you, Dez Bryant -- are good at scoring touchdowns. But, across the entire NFL, finding the end zone is something that mostly stems from opportunity. And, of course, a little bit of luck.

Remember Calvin Johnson's historic 2012 campaign? You know, the one where he almost hit the 2,000-yard mark in receiving? That year, Megatron scored five -- that's five -- touchdowns. Despite the fact that he caught more than a mile worth of yards, he found the end zone five times. He was unlucky -- he was tackled within the five-yard line eight times that season.

It goes the other way, too. In 2013, Jerricho Cotchery scored 10 touchdowns on just 602 yards receiving. Clearly, that was an outlier -- he regressed to the mean the next season in Carolina, scoring once with just 22 fewer yards.

Math is real.

Yards are one way to normalize touchdown production, but to be more accurate, we can also use our Net Expected Points (NEP) metric, which you can read more about in our glossary. Specifically with wide receivers, Reception NEP measures the number of real points a player accumulates on all catches. Because this is fantasy football and we're only interested in cumulative volume, we'll work with that.

The Process

Charting the relationship between touchdowns and our Net Expected Points (NEP) metric -- which shows how many actual points a player adds for his team (check out more on NEP in our glossary) -- allowed for an analysis of how many touchdowns a player should have scored versus how many touchdowns a player actually scored. To put this another way, because Net Expected Points measures how many points a player actually scored for his team, it's not skewed by a counting statistic like touchdowns -- a touchdown scored from the 1-yard line isn't as impactful as a touchdown scored from the 40.

This, in turn, brought the following chart.

What we find with this trendline is the number of touchdowns a player would be expected to score based on his NEP totals. So, if a dude puts up 100 Net Expected Points, we'd generally expect him to score a little under eight touchdowns.

Update Through Week 7

Now that that's out of the way, let's take a look at players who should have more touchdowns than they currently do through seven weeks. (Note: Data does not include Thursday night's contest.)

Player

Reception NEP

Touchdowns

Should Have

Difference

Alshon Jeffery

39.41

0

2.79

2.79

Amari Cooper

45.36

1

3.25

2.25

John Brown

27.77

0

1.90

1.90

A.J. Green

47.72

2

3.43

1.43

Julian Edelman

21.44

0

1.41

1.41

Jarvis Landry

34.18

1

2.39

1.39

Chris Conley

19.12

0

1.23

1.23

Stefon Diggs

31.85

1

2.21

1.21

Marqise Lee

18.32

0

1.17

1.17

Vincent Jackson

16.07

0

1.00

1.00

Quincy Enunwa

28.98

1

1.99

0.99

Quinton Patton

15.74

0

0.97

0.97

Adam Humphries

15.33

0

0.94

0.94

Pierre Garcon

28.31

1

1.94

0.94

Kenny Britt

39.60

2

2.81

0.81

Victor Cruz

26.36

1

1.79

0.79

Ted Ginn Jr.

13.17

0

0.77

0.77

Tajae Sharpe

13.17

0

0.77

0.77

Dorial Green-Beckham

13.14

0

0.77

0.77

Philly Brown

12.75

0

0.74

0.74

And here's a list of wide receivers who should have fewer touchdowns than they currently have:

Player

Reception NEP

Touchdowns

Should Have

Difference

Jordy Nelson

29.50

5

2.03

-2.97

Larry Fitzgerald

39.04

5

2.77

-2.23

Seth Roberts

14.41

3

0.87

-2.13

Antonio Brown

44.62

5

3.19

-1.81

Michael Crabtree

44.72

5

3.20

-1.80

Justin Hunter

6.23

2

0.24

-1.76

Andre Holmes

6.36

2

0.25

-1.75

Tyreek Hill

7.48

2

0.33

-1.67

Brice Butler

7.90

2

0.37

-1.63

Michael Floyd

21.50

3

1.41

-1.59

Justin Hardy

10.20

2

0.54

-1.46

Andre Johnson

11.39

2

0.64

-1.36

Brian Quick

24.75

3

1.66

-1.34

Torrey Smith

12.00

2

0.68

-1.32

Devin Funchess

12.45

2

0.72

-1.28

Kenny Stills

12.74

2

0.74

-1.26

Brandon LaFell

26.44

3

1.79

-1.21

Jamison Crowder

27.39

3

1.87

-1.13

Danny Amendola

14.74

2

0.89

-1.11

You can do what you want with this data -- it's here to simply show regression. But, generally speaking, the first list includes players you may want to considering buying in fantasy football, while the bottom one shows wideouts you may want to sell.